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Direct linkTelevantou, Ioulia; Marsh, Herbert W.; Kyriakides, Leonidas; Nagengast, Benjamin; Fletcher, John; Malmberg, Lars-Erik – School Effectiveness and School Improvement, 2015
The main objective of this study was to quantify the impact of failing to account for measurement error on school compositional effects. Multilevel structural equation models were incorporated to control for measurement error and/or sampling error. Study 1, a large sample of English primary students in Years 1 and 4, revealed a significantly…
Descriptors: Hierarchical Linear Modeling, Statistical Bias, Error of Measurement, Educational Research
Morin, Alexandre J. S.; Marsh, Herbert W.; Nagengast, Benjamin; Scalas, L. Francesca – Journal of Experimental Education, 2014
Many classroom climate studies suffer from 2 critical problems: They (a) treat climate as a student-level (L1) variable in single-level analyses instead of a classroom-level (L2) construct in multilevel analyses; and (b) rely on manifest-variable models rather than on latent-variable models that control measurement error at L1 and L2, and sampling…
Descriptors: Classroom Environment, Hierarchical Linear Modeling, Structural Equation Models, Grade 5
